Quantitative Analyst (Client Solutions)

Responsibilities Help clients translate our data into actual strategies, working on portfolio construction, backtesting approaches, signal generation, and turning raw forecasts into something tradeable.

Serve as a primary technical point of contact for our quantitative clients, fielding questions on data quality, methodology, coverage, and how to work with our datasets.

Write and publish research articles, data notes, and worked examples that showcase the value in Intropic's data to a technical audience.

Build reproducible examples and analysis in Python to support, illustrate and aid in your research process.

Investigate and resolve data-related issues clients raise, working with our research and engineering teams to get to the truth quickly.

Bring client feedback back to our product and research teams to help shape their priorities.

Requirements Strong working proficiency in Python and particularly Pandas. Comfortable working in Jupyter notebooks, with hands-on experience on data science projects.

Bachelor's or Master's degree in a STEM subject from a top university (preference towards Mathematics, Physics, Engineering, Economics or Finance), with a solid quantitative foundation built through study and/or work experience.

Genuine interest in finance and capital markets, and the ability to learn new concepts fast.

Excellent written communication: able to explain a technical result clearly to a sophisticated audience and produce publishable research.

Meticulous attention to detail and sound judgment when working under time pressure or with incomplete information.

Nice to Have Experience within quantitative finance, either through a sales, trading or a research role.

Familiarity with index methodologies (MSCI, S&P, FTSE etc.) and passive fund mechanics.

Active use of GitHub and version control; exposure to backtesting or research frameworks.

Prior familiarity with SQL and navigating sprawling data sets across platforms.

Prior experience in a client-facing, research, data science or sales-engineering role at a financial data or trading firm.